Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
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Bibliographic record
Abstract
BackgroundDespite a substantial reduction in the use of solid fuels worldwide, exposure to household air pollution (HAP) from use of these fuels for cooking remains a leading risk factor for global disease burden. Among environmental risk factors, the contribution of HAP to disease burden is second only to ambient particulate matter pollution. We present updates to our modeling methodology as well as our latest findings on attributable burden estimates.MethodsWe estimated HAP-attributable burden for cataract, chronic obstructive pulmonary disease, ischaemic heart disease, lower respiratory infections, lung cancer, neonatal disorders, stroke, and type 2 diabetes for 204 countries and territories from 1990 to 2019. We used spatio-temporal Gaussian Process Regression to model data from observational surveys and censuses reporting primary cooking fuel to estimate the proportion of individuals using a specific solid-fuel type (wood, coal/charcoal, agricultural residues, or dung) by location. We converted the fuel exposure estimates to year, location, and sex/age-specific PM2·5 exposures with a regression mapping function using household air pollution measurements. Using a Bayesian meta-regression tool, we estimated relative risk as a function of PM2·5 exposure for each disease based upon a systematic review of the epidemiological literature on indoor and ambient air pollution. We then combined our exposure estimates and relative risks to estimate population attributable fractions and attributable burden for each cause.FindingsIn 2019, 91·5 million global disability-adjusted life years (DALYs) (95% uncertainty interval 67·0–119) were attributable to HAP, a decline of more than 50% from 1990. We estimated 2·31 million (1·63–3·12) global deaths were attributable to HAP and accounted for over 4% of all deaths in 2019. HAP-attributable burden remains highest in sub-Saharan Africa and south Asia, with 3770·3 (2876·4–4720·2) and 2068·0 (1412·5–2799·7) age-standardised DALYs per 100 000 population, respectively.InterpretationAlthough the disease burden attributable to HAP decreased considerably between 1990 and 2019, it remains a significant risk factor. Our internally consistent methodology and comprehensive approach to estimation of HAP-attributable burden provides a robust resource for global health interventions. Efforts to transition to cleaner household energy sources should be accelerated.FundingBill & Melinda Gates Foundation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it